





import os

import pytest
from attr import dataclass


_UpperCamelCase							=			"""us-east-1"""  # defaults region




@dataclass
class 					_lowerCamelCase			:



      """simple docstring"""






      UpperCAmelCase_    :   str
      UpperCAmelCase_    :   Optional[Any]      ="""arn:aws:iam::558105141721:role/sagemaker_execution_role"""
      UpperCAmelCase_    :   Optional[Any]      ={
          """task_name""": """mnli""",
          """per_device_train_batch_size""": 16,
          """per_device_eval_batch_size""": 16,
          """do_train""": True,
          """do_eval""": True,
          """do_predict""": True,
          """output_dir""": """/opt/ml/model""",
          """overwrite_output_dir""": True,
          """max_steps""": 500,
          """save_steps""": 5_500,
      }
      UpperCAmelCase_    :   List[str]      ={**hyperparameters, """max_steps""": 1_000}







      @property
      def     UpperCAmelCase		(			self )							-> List[Any]:






        '''simple docstring'''






        if self.framework == "pytorch":
          return [
              {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
              {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
              {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
          ]
        else:
          return [
              {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
              {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
              {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
          ]







      @property
      def     UpperCAmelCase		(			self )							-> Union[str, Any]:






        '''simple docstring'''






        return F"""{self.framework}-transfromers-test"""







      @property
      def     UpperCAmelCase		(			self )							-> Optional[int]:






        '''simple docstring'''






        return F"""./tests/sagemaker/scripts/{self.framework}"""







      @property
      def     UpperCAmelCase		(			self )							-> Optional[int]:






        '''simple docstring'''






        if self.framework == "pytorch":
          return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
        else:
          return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"







@pytest.fixture(scope="class"					)
def    lowerCAmelCase__(						lowercase							:     Union[str, Any]					)			->     Dict:
  __snake_case :					Dict          =							SageMakerTestEnvironment(framework=request.cls.framework					)


"""simple docstring"""



import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


SCREAMING_SNAKE_CASE__:Dict									=			logging.get_logger(__name__)






class  snake_case__      (       snake_case_       ):


 def __init__( self    ,		*lowerCamelCase    ,		**lowerCamelCase						):
        warnings.warn(
            "The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
            " use DonutImageProcessor instead."    ,		lowerCamelCase    ,		)
        super().__init__(*lowerCamelCase    ,		**lowerCamelCase						)
